As mentioned earlier, in our experiments on the block-design dataset we use the dataset splits of [1]}, with 80% of the data used for training, 10% for validation and 10% for test.
We employ a standard cross-entropy loss function, minimized through mini-batch gradient descent using the Adam optimizer, with a learning rate of 0.001, and a mini-batch size of 16. Training was carried out for 200 epochs. Test accuracy is reported at the lowest validation accuracy.
